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Extractive summarization using siamese hierarchical transformer encoders
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Desarrollo de algoritmos para el aprendizaje automático de palabras en idiomas desconocidos a partir de audio.
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Summarization of Spanish Talk Shows with Siamese Hierarchical Attention Networks
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Siamese hierarchical attention networks for extractive summarization
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ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation
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Detección automática de segmentos acústicos e inferencia de unidades lingüísticas.
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Traducción Automática usando conocimiento semántico en un dominio restringido ; Automatic translation using semantic knowledge in a restricted domain
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Traducción Automática usando conocimiento semántico en un dominio restringido ; Automatic translation using semantic knowledge in a restricted domain
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A Train-on-Target Strategy for Multilingual Spoken Language Understanding
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A Strategy for Multilingual Spoken Language Understanding Based on Graphs of Linguistic Units
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| 11 |
Multilingual Spoken Language Understanding using graphs and multiple translations
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Exploiting multiple ASR outputs for a spoken language understanding task
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Abstract:
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-01931-4_19 ; In this paper, we present an approach to Spoken Language Understanding, where the input to the semantic decoding process is a composition of multiple hypotheses provided by the Automatic Speech Recognition module. This way, the semantic constraints can be applied not only to a unique hypothesis, but also to other hypotheses that could represent a better recognition of the utterance. To do this, we have developed an algorithm to combine multiple sentences into a weighted graph of words, which is the input to the semantic decoding process. It has also been necessary to develop a specific algorithm to process these graphs of words according to the statistical models that represent the semantics of the task. This approach has been evaluated in a SLU task in Spanish. Results, considering different configurations of ASR outputs, show the better behavior of the system when a combination of hypotheses is considered. ; This work is partially supported by the Spanish MICINN under contract TIN2011-28169-C05-01, and under FPU Grant AP2010-4193 ; Calvo Lance, M.; García Granada, F.; Hurtado Oliver, LF.; Jiménez Serrano, S.; Sanchís Arnal, E. (2013). Exploiting multiple ASR outputs for a spoken language understanding task. En Speech and Computer. Springer Verlag (Germany). 8113:138-145. https://doi.org/10.1007/978-3-319-01931-4_19 ; S ; 138 ; 145 ; 8113 ; Tür, G., Mori, R.D.: Spoken Language Understanding: Systems for Extracting Semantic Information from Speech, 1st edn. Wiley (2011) ; Fiscus, J.G.: A post-processing system to yield reduced word error rates: Recognizer output voting error reduction (ROVER). In: Proceedings of the 1997 IEEE Workshop on Automatic Speech Recognition and Understanding, pp. 347–354. IEEE (1997) ; Larkin, M.A., Blackshields, G., Brown, N.P., Chenna, R., McGettigan, P.A., McWilliam, H., Valentin, F., Wallace, I.M., Wilm, A., Lopez, R., Thompson, J.D., Gibson, T.J., Higgins, D.G.: ClustalW and ClustalX version 2.0. Bioinformatics 23, 2947–2948 (2007) ; Sim, K.C., Byrne, W.J., Gales, M.J.F., Sahbi, H., Woodland, P.C.: Consensus network decoding for statistical machine translation system combination. In: IEEE Int. Conference on Acoustics, Speech, and Signal Processing (2007) ; Bangalore, S., Bordel, G., Riccardi, G.: Computing Consensus Translation from Multiple Machine Translation Systems. In: Proceedings of IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2001), pp. 351–354 (2001) ; Calvo, M., Hurtado, L.-F., García, F., Sanchís, E.: A Multilingual SLU System Based on Semantic Decoding of Graphs of Words. In: Torre Toledano, D., Ortega Giménez, A., Teixeira, A., González Rodríguez, J., Hernández Gómez, L., San Segundo Hernández, R., Ramos Castro, D. (eds.) IberSPEECH 2012. CCIS, vol. 328, pp. 158–167. Springer, Heidelberg (2012) ; Hakkani-Tür, D., Béchet, F., Riccardi, G., Tür, G.: Beyond ASR 1-best: Using word confusion networks in spoken language understanding. Computer Speech & Language 20, 495–514 (2006) ; Benedí, J.M., Lleida, E., Varona, A., Castro, M.J., Galiano, I., Justo, R., López de Letona, I., Miguel, A.: Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: DIHANA. In: Proceedings of LREC 2006, Genoa, Italy, pp. 1636–1639 (2006)
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Keyword:
Combination of multiple outputs; Graph of concepts; Graph of words; LENGUAJES Y SISTEMAS INFORMATICOS; Spoken Language Understanding
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URL: http://hdl.handle.net/10251/38611
https://doi.org/10.1007/978-3-319-01931-4_19
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| 15 |
ELIRF at MEDIAEVAL 2013: Similar Segments of Social Speech Task
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A phonetic-based approach to query-by-example spoken term detection
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Using word graphs as intermediate representation of uttered sentences
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A multilingual SLU system based on semantic decoding of graphs of words
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Language modelization and categorization for voice-activated QA
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